- Generally underutilized in the credit risk area. Particularly useful for testing metrics where there is little consensus on standard error or when statistical testing procedures are absent.
Advantages:
Disadvantages:
Dataset:
## Bin Base Target PSI
## 1 1 0.22 0.35 0.18
## 2 2 0.24 0.31 0.18
## 3 3 0.07 0.05 0.18
## 4 4 0.48 0.29 0.18
Testing Hypothesis:
What is the probability that PSI value is less or equal to 0.15?
Visualization:
## p-value = 21.26%
Dataset:
## Rating Grade # obs. DR
## 1 01 (-Inf,0.0199) 202 0.01
## 2 02 [0.0199,0.0263) 54 0.02
## 3 03 [0.0263,0.0369) 96 0.03
## 4 04 [0.0369,0.0903) 204 0.06
## 5 05 [0.0903,0.15) 103 0.11
## 6 06 [0.15,0.197) 41 0.12
## 7 07 [0.197,Inf) 50 0.32
Testing Hypothesis:
What is the probability that HHI value is greater or equal to 0.20?
Visualization:
## p-value = 23.72%
Dataset:
## Bootstrapped AUC summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.6769 0.7414 0.7526 0.7525 0.7638 0.8067
## Development sample AUC 79%.
## Application portfolio AUC 75.2%.
Testing Hypothesis:
What is the probability that the application portfolio AUC is equal to 79%?
Figure 1.
Figure 2.
## p-value = 2.26%